摘要：The study of companion (pet) dogs is an area of great translational potential, as they share a risk for many conditions that afflict humans. Among these are conditions that affect sleep, including chronic pain and cognitive dysfunction. Significant advancements have occurred in the ability to study sleep in dogs, including development of non-invasive polysomnography; however, basic understanding of dog sleep patterns remains poorly characterized. The purpose of this study was to establish baseline sleep–wake cycle and activity patterns using actigraphy and functional linear modeling (FLM), for healthy, adult companion dogs. Forty-two dogs were enrolled and wore activity monitors for 14 days. FLM demonstrated a bimodal pattern of activity with significant effects of sex, body mass, and age; the effect of age was particularly evident during the times of peak activity. This study demonstrated that FLM can be used to describe normal sleep–wake cycles of healthy adult dogs and the effects of physiologic traits on these patterns of activity. This foundation makes it possible to characterize deviations from normal patterns, including those associated with chronic pain and cognitive dysfunction syndrome. This can improve detection of these conditions in dogs, benefitting them and their potential as models for human disease.
其他摘要：Abstract The study of companion (pet) dogs is an area of great translational potential, as they share a risk for many conditions that afflict humans. Among these are conditions that affect sleep, including chronic pain and cognitive dysfunction. Significant advancements have occurred in the ability to study sleep in dogs, including development of non-invasive polysomnography; however, basic understanding of dog sleep patterns remains poorly characterized. The purpose of this study was to establish baseline sleep–wake cycle and activity patterns using actigraphy and functional linear modeling (FLM), for healthy, adult companion dogs. Forty-two dogs were enrolled and wore activity monitors for 14 days. FLM demonstrated a bimodal pattern of activity with significant effects of sex, body mass, and age; the effect of age was particularly evident during the times of peak activity. This study demonstrated that FLM can be used to describe normal sleep–wake cycles of healthy adult dogs and the effects of physiologic traits on these patterns of activity. This foundation makes it possible to characterize deviations from normal patterns, including those associated with chronic pain and cognitive dysfunction syndrome. This can improve detection of these conditions in dogs, benefitting them and their potential as models for human disease.
